Strategic ML Deployment Engineer

Google LLC; Mountain View, New York (CA, NY); On-site; USD 174,000 - 232,000; Full time

Job summary

Google DeepMind seeks a Forward Deployed Engineer for Kaggle to onboard external benchmarks and drive joint evaluations across partner datasets. You will build tools and documentation that surface performance signals to model teams, enabling faster iteration and deeper integration with partner platforms.

The role emphasizes collaboration with engineering, product, and external stakeholders, with responsibilities spanning end-to-end benchmark onboarding and the creation of high-visibility

Qualifications

• Bachelor's degree or equivalent practical experience.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
• Experience with Machine Learning systems or Large Language Models (LLMs).
• Experience in a customer-facing role, managing client relationships or external stakeholders.

Responsibilities

• Own the end-to-end onboarding of critical new benchmarks to the Kaggle platform.
• Drive joint evaluations and benchmarking, build and run systematic evals on partner-specific datasets to deliver high-fidelity performance signals directly to modeling teams.
• Author high-visibility case studies, developer blogs, and reference implementations to showcase Gemini’s production capabilities.
• Build feedback loop tooling, collaborate with product engineering to develop tooling that aggregates and surfaces developer feedback patterns at scale.

Skills

ML systems/LLMs

Customer-facing

Software testing/launching

Stakeholder management

Education

Bachelor's degree or equivalent practical experience

Tools

APIs

SDKs

Developer tools

Job description

Google DeepMind seeks a Forward Deployed Engineer for Kaggle to onboard external benchmarks and drive joint evaluations across partner datasets. You will build tools and documentation that surface performance signals to model teams, enabling faster iteration and deeper integration with partner platforms.

The role emphasizes collaboration with engineering, product, and external stakeholders, with responsibilities spanning end-to-end benchmark onboarding and the creation of high-visibility